decevf {pastecs} | R Documentation

## Time series decomposition using eigenvector filtering (EVF)

### Description

The eigenvector filtering decomposes the signal by applying a principal component analysis (PCA) on the original signal and a certain number of copies of it incrementally lagged, collected in a multivariate matrix. Reconstructing the signal using only the most representative eigenvectors allows filtering it.

### Usage

    decevf(x, type="additive", lag=5, axes=1:2)

### Arguments

`x` | a regular time series ('rts' under S+ and 'ts' under R)
`type` | the type of model, either `type="additive"` (by default), or `type="multiplicative"`
`lag` | The maximum lag used. A PCA is run on the matrix constituted by vectors lagged from 0 to `lag`. The defaulf value is 5, but a value corresponding to no significant autocorrelation, on basis of examination of the autocorrelation plot obtained by `acf` in the library 'ts' should be used (Lag at first time the autocorrelation curve crosses significance lines multiplied by the frequency of the series).
`axes` | The principal axes to use to reconstruct the filtered signal. For instance, to use axes 2 and 4, use `axes=c(2,4)`. By default, the first two axes are considered (`axes=1:2`)

### Value

a 'tsd' object

### Author(s)

Frédéric Ibanez (ibanez@obs-vlfr.fr), Philippe Grosjean (phgrosjean@sciviews.org)

### References

Colebrook, J.M., 1978. Continuous plankton records: zooplankton and environment, North-East Atlantic and North Sea 1948-1975. Oceanologica Acta, 1:9-23.

Ibanez, F. & J.C. Dauvin, 1988. Long-term changes (1977-1987) on a muddy fine sand Abra alba - Melinna palmate population community from the Western English Channel. J. Mar. Prog. Ser., 49:65-81.

Ibanez, F., 1991. Treatment of data deriving from the COST 647 project on coastal benthic ecology: The within-site analysis. In: B. Keegan (ed.) Space and time series data analysis in coastal benthic ecology. Pp. 5-43.

Ibanez, F. & M. Etienne, 1992. Le filtrage des séries chronologiques par l'analyse en composantes principales de processus (ACPP). J. Rech. Océanogr., 16:27-33.

Ibanez, F., J.C. Dauvin & M. Etienne, 1993. Comparaison des évolutions à long-terme (1977-1990) de deux peuplements macrobenthiques de la Baie de Morlaix (Manche Occidentale): relations avec les facteurs hydroclimatiques. J. Exp. Mar. Biol. Ecol., 169:181-214.

### See Also

`tsd`, `tseries`, `decaverage`, `deccensus`, `decmedian`, `decdiff`, `decreg`, `decloess`

### Examples

    data(releve)
    melo.regy <- regul(releve$Day, releve$Melosul, xmin=9, n=87,
            units="daystoyears", frequency=24, tol=2.2, methods="linear",
            datemin="21/03/1989", dateformat="d/m/Y")
    melo.ts <- tseries(melo.regy)
    acf(melo.ts)
    # Autocorrelation is not significant after 0.16
    # That corresponds to a lag of 0.16*24=4 (frequency=24)
    melo.evf <- decevf(melo.ts, lag=4, axes=1)
    plot(melo.evf, col=c(1, 4, 2))
    # A superposed graph is better in the present case
    plot(melo.evf, col=c(1, 4), xlab="stations", stack=FALSE, resid=FALSE,
            lpos=c(0, 60000))

[Package pastecs version 1.3-2 Index]